Rabbani, Muhammad Zachrie (2025) ANALISIS KLASIFIKASI KINERJA PENGIRIMAN DANPENGARUH TERHADAP KEPUASAN PELANGGAN (STUDI KASUS : PT. BATHI DUA PUTRA). S1 thesis, Universitas Mercu Buana-Menteng.
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Abstract
Pemanfaatan teknologi informasi berkembang pesat, terutama di bidang pengiriman barang yang semakin penting seiring meningkatnya kebutuhan logistik, termasuk e-commerce dan kebutuhan harian. Inovasi memungkinkan perusahaan memantau dan mengevaluasi performa layanan lebih efektif. Penelitian sebelumnya banyak menilai ketepatan waktu dengan machine learning, namun terbatas pada aspek waktu, tanpa memperhatikan tipe layanan (reguler, ekspres, same-day) yang memengaruhi ekspektasi pengguna. Selain itu, kepuasan pelanggan belum diukur secara menyeluruh, padahal dipengaruhi juga oleh respons keluhan, keamanan barang, dan transparansi pengiriman. Penelitian ini mengusulkan model berbasis machine learning yang tidak hanya mengevaluasi ketepatan waktu, tetapi juga mengukur kepuasan pelanggan secara komprehensif. Model ini diharapkan mengidentifikasi faktor kritis kepuasan pengguna dan membantu perusahaan meningkatkan performa layanan sesuai ekspektasi. The use of information technology is rapidly growing, particularly in parcel delivery, which has become increasingly important alongside the rising demand for logistics, including e-commerce and daily needs. Innovation enables logistics companies to monitor and evaluate service performance more effectively. Previous studies mostly assessed timeliness using machine learning, but remained limited to delivery time, without considering service types (regular, express, or same-day) that significantly influence user expectations. Furthermore, overall customer satisfaction has not been thoroughly measured, even though it is also affected by complaint handling, shipment security, and delivery transparency. This study proposes a machine learning-based model that not only evaluates timeliness but also comprehensively measures customer satisfaction, identifies critical factors, and helps companies improve service performance.
| Item Type: | Thesis (S1) |
|---|---|
| NIM/NIDN Creators: | 41821010083 |
| Uncontrolled Keywords: | ketepatan waktu, metode klasifikasi, kepuasan pelanggan, machine learning punctuality, classification methods, customer satisfaction, machine learning |
| Subjects: | 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 005 Computer Programmming, Programs, Data/Pemprograman Komputer, Program, Data > 005.2 Programming for Specific Computers, for Specific Operating Systems, for Specific User Interface/Pemrograman untuk Tipe Komputer, Sistem Operasi dan Tampilan Antar Muka Pengguna Tertentu |
| Divisions: | Fakultas Ilmu Komputer > Sistem Informasi |
| Depositing User: | ZAIRA ELVISIA |
| Date Deposited: | 09 Sep 2025 03:42 |
| Last Modified: | 09 Sep 2025 03:42 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/97580 |
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